When reading newspapers, documents, or web pages, there are significant amounts of text in which salient information is imbedded. For people with low vision, dyslexia, blindness, some eye-motor disabilities, and most cognitive deficiencies, text density and organization create challenges. Not only is there a huge cognitive processing demand required, but the individual must parse meaningful information from non-meaningful information without the benefit of additional cueing (e.g., color, chunking, etc). In addition, the blind person using a screen reading device must perform this higher level cognitive function while also listening to the information, making it necessary to retain large quantities of spoken information in working memory buffers to derive the meaning contained within a few key words.
Typical industry solutions to date utilize a document summarizer. Summarization technology addresses the problem of information overload by reducing a full document to a surrogate summary consisting of a few sentences extracted from the document in a way which retains the essence of the document content. Summarization technology addresses technical challenges like coherence, cohesion, and information quotient. However, even though the information reduction it achieves would help a person with cognitive disabilities, summarization does not explicitly address perceptual problems which might require solutions identifying salient text fragments of granularity smaller than a sentence.
In particular, none of the summarization technologies listed above ‘tag’ words or phrases with a salience measure. Consequently, these technologies are unable to focus on short text fragments; brevity being of the essence from the point of view of a person with cognitive disabilities. Furthermore, not much attention has been paid to contextualizing the salient fragments. Summarization solutions do not, typically, relate a summary to the original document source, which makes it hard to create a cognitive map between the summary and the full text.
Therefore, there is a need for a solution to reduce the heavy cognitive load, addressing at least some of the problems associated with conventional document summarizers.